A comprehensive survey on machine learning for workplace injury analysis: risk prediction, return to work strategies, and demographic insights by Gonzalo A. Vivian, Richard A. Bauder, Taghi M. Khoshgoftaar

“…It emphasizes the importance of leveraging ML in personalized RTW programs, which use data-driven insights to improve recovery outcomes and reduce economic demands. …”
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Classification of oil palm tree conditions from UAV imagery using the YOLO object detector by Aakash Thapa, Teerayut Horanont, Bipul Neupane, Jirawan Klaylee, Apichon Witayangkurn

“…While existing remote sensing data and deep learning methods offer efficient alternatives for monitoring, achieving a highly accurate tree condition classification remains a challenge. …”
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Fusing MODIS and AVHRR products to generate a global 1-km continuous NDVI time series covering four decades by Xiaobin Guan, Huanfeng Shen, Yuchen Wang, Dong Chu, Xinghua Li, Linwei Yue, Wei Li, Xinxin Liu, Liangpei Zhang

“…Simulated comparison with MODIS data and real-data assessments with true 1 km AVHRR data both confirm the ideal accuracy of the fusion product in spatial distribution and temporal variation, providing stable long-term results similar to MODIS data. …”
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Discretization-independent surrogate modeling of physical fields around variable geometries using coordinate-based networks by James Duvall, Karthik Duraisamy

“…Numerical solutions of partial differential equations require expensive simulations, limiting their application in design optimization, model-based control, and large-scale inverse problems. …”
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A high-quality chromosome-level genome assembly of Antiaris toxicaria by Weicheng Huang, Jiaxin Xiang, Yamei Ding, Wanzhen Liu, Ni Fang, Yongmei Xiong, Seping Dai, Hui Yu

“…Its latex contains various cardiac glycosides, which hold significant research and potential application value. However, the lack of genomic resources for A. toxicaria currently hinders molecular genetic studies on its medicinal components. …”
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Simulation of lake underwater terrain based on the XGBoost model: a case study of typical lakes on the Tibetan Plateau by Kaixin Hu, Shanlong Lu, Qing Li, Cong Du, Bo Zhang, Peng Du, Harrison Odion Ikhumhen

“…Although the traditional measurement approaches are capable of precisely acquiring underwater terrain data, they are costly and time-consuming, making them impractical for widespread application to all lake water bodies. …”
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ADOPTION OF CLIMATE-SMART AGRICULTURAL PRACTICES: EMPIRICAL EVIDENCE AMONG VEGETABLE FARMERS IN BASSA, NIGERIA by Godfrey C. Onuwaa, Oludare Adediireb, Cletus Ajomac, Ganiyu Binuyoa

“…Vegetable farmers were selected using multistage sampling techniques. Primary data collected was analyzed using descriptive statistics, weighted average index and adoption index techniques. …”
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The present situation and shifts observed in wetlands within the St. Lawrence Seaway region of Canada, utilizing imagery from the Landsat archive and the cloud-based platform Googl... by Meisam Amani, Mohammad Kakooei, Rebecca Warren, Sahel Mahdavi, Kevin Murnaghan, Arsalan Ghorbanian, Amin Naboureh

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OCT-SelfNet: a self-supervised framework with multi-source datasets for generalized retinal disease detection by Fatema-E Jannat, Sina Gholami, Minhaj Nur Alam, Hamed Tabkhi

“…By employing a robust two-phase training strategy self-supervised pre-training with unlabeled data followed by a supervised training stage, we utilized the power of a masked autoencoder built on the SwinV2 backbone.ResultsExtensive experiments were conducted across three datasets with varying encoder backbones, assessing scenarios including the absence of self-supervised pre-training, the absence of data fusion, low data availability, and unseen data to evaluate the efficacy of our methodology. …”
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Improving time upscaling of instantaneous evapotranspiration based on machine learning models by Danni Yang, Shanshan Yang, Jiaojiao Huang, Shuyu Zhang, Sha Zhang, Jiahua Zhang, Yun Bai

“…These findings support the application of ML models in ET upscaling, enabling ET estimation across large spatiotemporal scales.…”
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Evaluating Sex and Age Biases in Multimodal Large Language Models for Skin Disease Identification from Dermatoscopic Images by Zhiyu Wan, Yuhang Guo, Shunxing Bao, Qian Wang, Bradley A. Malin

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Unveiling the complete genome sequence of Paenibacillus taichungensis: genomic features and biocontrol potential by Shanwen Ding, Zijun Ma, Yafei Tang, Lin Yu, Zifu He, Xiaoman She

“…However, the research data and application cases of Paenibacillus taichungensis were still poorly understood. …”
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Machine learning and uncertainty quantification to track and monitor natural frequencies in vibration-based SHM applied to offshore wind turbines by Maximillian Weil, Carlos Sastre Jurado, Wout Weijtjens, Christof Devriendt

“…This study uses virtual ensembles for UQ through the variance between multiple truncated submodel predictions. Practical application to monopile-supported OWT data demonstrates the tracking abilities, separating structural modes from rotor dynamics. …”
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Unraveling deep-learning detection of atmospheric Kármán vortex streets: dataset, baseline benchmarking, and optimization by Yihan Zhang, Chaoyue Wu, Qiao Su, Yuqi Zhang, Daoyi Chen

“…This network, built upon a custom-designed mini-ResNet dual-level classification network and trained on MODIS HDF-format sensor data, demonstrates that the dataset is particularly suited for detecting Kármán vortex streets in cloudy conditions. …”
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Enhancing hepatopathy clinical trial efficiency: a secure, large language model-powered pre-screening pipeline by Xiongbin Gui, Hanlin Lv, Xiao Wang, Longting Lv, Yi Xiao, Lei Wang

“…While AI-powered pre-screening offers potential solutions, challenges remain regarding accuracy, efficiency, and data privacy. Methods We developed a novel patient pre-screening pipeline that leverages clinical expertise to guide the precise, safe, and efficient application of large language models. …”
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Can open source large language models be used for tumor documentation in Germany?—An evaluation on urological doctors’ notes by Stefan Lenz, Arsenij Ustjanzew, Marco Jeray, Meike Ressing, Torsten Panholzer

“…Evaluating LLMs in the German medical domain, especially their ability to interpret specialized language, is essential to determine their suitability for the use in clinical documentation. Due to data protection regulations, only locally deployed open source LLMs are generally suitable for this application. …”
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ECG-LM: Understanding Electrocardiogram with a Large Language Model by Kai Yang, Massimo Hong, Jiahuan Zhang, Yizhen Luo, Suyuan Zhao, Ou Zhang, Xiaomao Yu, Jiawen Zhou, Liuqing Yang, Ping Zhang, Mu Qiao, Zaiqing Nie

“…Methods: Although recent advancements in multi-modal large language modeling have propelled their application scope beyond the natural language processing domain, their applicability to ECG processing remains largely unexplored, partly due to the lack of text–ECG data. …”
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A dataset of the abundance of Ixodes spp. ticks in forests of the Auvergne-Rhône-Alpes Region (France) by Isabelle Lebert, Valérie Poux, Magalie René-Martellet, Karine Chalvet-Monfray, Gwenael Vourc'h, Séverine Bord

“…One approach that can be employed to account for the impact of these factors on variations in sampling rate is the use of removal samplings, i.e. several successive samplings.The TELETIQ project (https://teletiq.clermont.hub.inrae.fr/) was interested in mobile phone and participatory science data for the estimation and understanding of the risk of transmission of environmental diseases with an application to diseases transmitted by ticks. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

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A machine learning approach of exploring nexus between geopolitical risk and Indian economic uncertainty: a comparative review by Bharat Kumar Meher, Abhishek Anand, Virgil Popescu, Ramona Birau, Iuliana Carmen Bărbăcioru

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